logarithmic sobolev inequalities (lsis) show up in several areas of analysis; in particular, in probability. in this talk i will give some background and applications of lsis. i will also discuss some recent work and show how lsis can be used to give a new proof of the classical result that the empirical law of eigenvalues of a sequence of random matrices converges weakly to its mean in probability.